{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "29bb38b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import confusion_matrix, accuracy_score, precision_score, recall_score, f1_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b4432dec",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "14238beb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_dataset(path: str, train: bool=True, is_static=None) -> tuple[np.ndarray, np.ndarray]:\n",
    "    label = \"train\" if train else \"test\"\n",
    "    acc_x = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_acc_x_{label}.txt\"), dtype=np.float32)\n",
    "    acc_y = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_acc_y_{label}.txt\"), dtype=np.float32)\n",
    "    acc_z = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_acc_z_{label}.txt\"), dtype=np.float32)\n",
    "    gyro_x = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_gyro_x_{label}.txt\"), dtype=np.float32)\n",
    "    gyro_y = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_gyro_y_{label}.txt\"), dtype=np.float32)\n",
    "    gyro_z = np.loadtxt(os.path.join(path, label, \"Inertial Signals\", f\"body_gyro_z_{label}.txt\"), dtype=np.float32)\n",
    "    assert acc_x.shape[0] == acc_y.shape[0] and acc_x.shape[0] == acc_z.shape[0] and acc_x.shape[0] == gyro_x.shape[0] and acc_x.shape[0] == gyro_y.shape[0] and acc_x.shape[0] == gyro_z.shape[0], \"All arrays must have the same length.\"\n",
    "    \n",
    "    X = np.stack((acc_x, acc_y, acc_z, gyro_x, gyro_y, gyro_z), axis=2)\n",
    "    y = np.loadtxt(os.path.join(path, label, f\"y_{label}.txt\"), dtype=np.int32) - 1\n",
    "    assert X.shape[0] == y.shape[0], \"The number of samples in X and y must be the same.\"\n",
    "\n",
    "    mean = np.array([-0.00066533, -0.00031751, -0.00020395, -0.0034113 , -0.00017161, 0.00089603], dtype=np.float32)\n",
    "    std = np.array([0.14196804, 0.08511718, 0.07230477, 0.26109824, 0.27211866, 0.17970076], dtype=np.float32)\n",
    "    X = (X - mean) / std\n",
    "\n",
    "    if is_static is not None:\n",
    "        if is_static:\n",
    "            filters = y > 2\n",
    "        else:\n",
    "            filters = y <= 2\n",
    "        X = X[filters]\n",
    "        y = y[filters]\n",
    "    return X, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d18d9874",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, y_train = read_dataset(\"../..//UCI-HAR Dataset\", train=True)\n",
    "X_test, y_test = read_dataset(\"../..//UCI-HAR Dataset\", train=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2e26044e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-07-17 20:10:04.220821: I metal_plugin/src/device/metal_device.cc:1154] Metal device set to: Apple M2\n",
      "2025-07-17 20:10:04.220956: I metal_plugin/src/device/metal_device.cc:296] systemMemory: 8.00 GB\n",
      "2025-07-17 20:10:04.220967: I metal_plugin/src/device/metal_device.cc:313] maxCacheSize: 2.67 GB\n",
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1752754204.221294  140246 pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.\n",
      "I0000 00:00:1752754204.221563  140246 pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)\n"
     ]
    }
   ],
   "source": [
    "model = tf.keras.models.load_model(\"../../Model.keras\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4189b946",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-07-17 20:10:04.838156: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:117] Plugin optimizer for device_type GPU is enabled.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m230/230\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 10ms/step\n",
      "\u001b[1m93/93\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 9ms/step\n"
     ]
    }
   ],
   "source": [
    "y_train_pred = tf.keras.backend.argmax(model.predict(X_train), axis=-1)\n",
    "y_test_pred = tf.keras.backend.argmax(model.predict(X_test), axis=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "37ecd661",
   "metadata": {},
   "outputs": [],
   "source": [
    "cm_train = confusion_matrix(y_train, y_train_pred)\n",
    "cm_test = confusion_matrix(y_test, y_test_pred)\n",
    "\n",
    "class_names = [\"Walking\", \"Walking Upstairs\", \"Walking Downstairs\", \"Sitting\", \"Standing\", \"Laying\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "32f5e109",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm_train, annot=True, fmt='d', cmap='Blues', xticklabels=class_names, yticklabels=class_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bba19f76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm_test, annot=True, fmt='d', cmap='Blues', xticklabels=class_names, yticklabels=class_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2bd1a0aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training: Accuracy: 0.3285, Precision: 0.7108, Recall: 0.3285, F1 Score: 0.2129\n"
     ]
    }
   ],
   "source": [
    "print(f\"Training: Accuracy: {accuracy_score(y_train, y_train_pred):.4f}, Precision: {precision_score(y_train, y_train_pred, average='weighted'):.4f}, Recall: {recall_score(y_train, y_train_pred, average='weighted'):.4f}, F1 Score: {f1_score(y_train, y_train_pred, average='weighted'):.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2955d5ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing: Accuracy: 0.3247, Precision: 0.5175, Recall: 0.3247, F1 Score: 0.2007\n"
     ]
    }
   ],
   "source": [
    "print(f\"Testing: Accuracy: {accuracy_score(y_test, y_test_pred):.4f}, Precision: {precision_score(y_test, y_test_pred, average='weighted'):.4f}, Recall: {recall_score(y_test, y_test_pred, average='weighted'):.4f}, F1 Score: {f1_score(y_test, y_test_pred, average='weighted'):.4f}\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "latest_nn",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
